Wei Huang

According to our database, Wei Huang authored at least 13 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

DBellQuant: Breaking the Bell with Double-Bell Transformation for LLMs Post Training Binarization.

Zijian Ye, Wei Huang, Yifei Yu, Tianhe Ren, Zhongrui Wang, Xiaojuan Qi

CoRR, July, 2025

MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO.

Yicheng Xiao, Lin Song, Yukang Chen, Yingmin Luo, Yuxin Chen, Yukang Gan, Wei Huang, Xiu Li, Xiaojuan Qi, Ying Shan

CoRR, May, 2025

Data Pruning by Information Maximization.

Haoru Tan, Sitong Wu, Wei Huang, Shizhen Zhao, Xiaojuan Qi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Mixture Compressor for Mixture-of-Experts LLMs Gains More.

Wei Huang, Yue Liao, Jianhui Liu, Ruifei He, Haoru Tan, Shiming Zhang, Hongsheng Li, Si Liu, Xiaojuan Qi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection.

Songhao Han, Wei Huang, Hairong Shi, Le Zhuo, Xiu Su, Shifeng Zhang, Xu Zhou, Xiaojuan Qi, Yue Liao, Si Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

An empirical study of LLaMA3 quantization: from LLMs to MLLMs.

Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

Vis. Intell., 2024

MC-MoE: Mixture Compressor for Mixture-of-Experts LLMs Gains More.

Wei Huang, Yue Liao, Jianhui Liu, Ruifei He, Haoru Tan, Shiming Zhang, Hongsheng Li, Si Liu, Xiaojuan Qi

CoRR, 2024

SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models.

Wei Huang, Haotong Qin, Yangdong Liu, Yawei Li, Xianglong Liu, Luca Benini, Michele Magno, Xiaojuan Qi

CoRR, 2024

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study.

Wei Huang, Xudong Ma, Haotong Qin, Xingyu Zheng, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

CoRR, 2024

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs.

Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SNNGX: Securing Spiking Neural Networks with Genetic XOR Encryption on RRAM-based Neuromorphic Accelerator.

Kwunhang Wong, Songqi Wang, Wei Huang, Xinyuan Zhang, Yangu He, Karl Ming Him Lai, Yuzhong Jiao, Ning Lin, Xiaojuan Qi, Xiaoming Chen, Zhongrui Wang

Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, 2024

2023

OHQ: On-chip Hardware-aware Quantization.

Wei Huang, Haotong Qin, Yangdong Liu, Jingzhuo Liang, Yifu Ding, Ying Li, Xianglong Liu

CoRR, 2023

An innovative experimental teaching method of hardware-software co-design-Taking a hardware accelerator of neural network using FPGA.

Ying Li, Jingzhuo Liang, Gui Shi Jie, Yangdong Liu, Wei Huang, Yue Yan, Xianglong Liu

Proceedings of the IEEE Frontiers in Education Conference, 2023